Charge VC
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Charge VC

Stats for Startups: How you can help!

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A week ago, we announced the launch of Stats for Startups, a collaboration between industry and academia to explore and mitigate bias in early-stage financing, beginning with the distribution of better benchmarks for common startup KPIs.

Within minutes of posting dozens of folks — academics, VCs, entrepreneurs, and journalists- reached out. Wow. Thank you!

While we’ve been working on the grant for almost a year (more on that), turns out that:

  1. Working closely with a number of partners to safely collect closely held, proprietary data
  2. Extracting it from thousands of disconnected pitch decks, call notes, online and offline databases
  3. Storing it very securely
  4. Cleaning and normalizing the raw data
  5. Defining a standardized set of KPIs from the data
  6. Connecting our KPIs to external data repositories to put it in context
  7. Figuring out the right questions to ask
  8. Making sense of the numbers
  9. Presenting potentially controversial results on a sensitive matter
  10. Sharing the learnings broadly

…is a fair amount of work!

To that end, we are always looking for help with the following:

Entrepreneurs that would like their startups analyzed and benchmarked. We are working toward a system in which you can send us your deck and we can return a structured output in which your KPIs are benchmarked against your peers. We’re not there yet, but we are getting closer. In the meantime, we’d love to know what types of information you are most interested in (valuation data, Operational KPIs, Diversity measures etc).

Venture Funds that would like to contribute historical (de-identified) data sets. We’ve spent months building and refining our process and schema and are putting together a handbook for firms that want to contribute. In the medium term, we’re looking to connect with managers at sector-focused firms to interview re: sectoral specific-KPIs.

Engineers who can help us think through the architecture for all of this scraping, cleaning, and structuring. We’re also looking for ML experts who can help us with the more predictive elements of the research.

Statisticians who can help us make sure that our analyses are applicable to the greater population.

Journalists and educators who are interested in open data, the dangers of AI bias, and data equity for under-represented populations.

Diverse perspectives beyond the narrow confines of the venture capital echo chamber that we’ve been living in for the past 15 years.

If you fit the bill on any of the above and are interested to learn more: please reach out to StatsforStartups at Charge dot vc.

Can’t wait to hear from you!

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NYC-based Pre-seed Venture Capital

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